基于累积前景理论的高速铁路差异化定价与坐席分配联合优化方法

Joint Optimization of Differential Pricing and Seat Allocation for High-speed Railway Based on Cumulative Prospect Theory

针对目前高速铁路票价机制单一,不能有效发挥客流引导调节作用和增加企业效益等不足,研究高速铁路客票差异化定价与坐席分配的联合优化决策方法。根据出行特征对高速铁路旅客进行市场细分,利用累积前景理论定量描述旅客出行选择行为中的有限理性规律,在综合票价、旅行时间、发车时刻和退票成本等因素的基础上构造价格弹性需求函数后,考虑列车能力、票价上下限、票价倒挂以及坐席分配数量等约束,以高速铁路客票总收益最大化为目标构建优化模型。结合模型特征,通过将票价倒挂约束进行多段映射罚函数处理后,设计改进的灰狼优化算法对模型进行求解与计算分析。针对京沪高速铁路进行的计算分析表明,在运输能力不变的情况下,所提出的客票定价和坐席分配的联合优化方法可使总客票收入提高4.76%。

In response to the shortcomings of the single high-speed railway pricing mechanism of high-speed railway that can not effectively guide passenger demand nor increase revenue growth, this paper divided the passenger market based on trip characteristics, described the bounded rationality in the choice behavior of passengers through cumulative prospect theory, and constructed an elastic demand function by using multiple logit discrete choice model. On the basis, a joint optimization method of differential pricing and seat allocation for high-speed railway was proposed, in which the objective was to maximize the revenue under the constrains of train’s capacity, pricing fluctuation range, no upside-down pricing and minimum seats number. The multistage assignment penalty function was used to deal with the model constraints, and an improved gray wolf optimization algorithm was designed to solve the model. The calculation results of the Beijing—Shanghai HSR show that the method can increase the total ticket revenue by 4.76% when the transport capacity of the high-speed railway remains unchanged. Overall, the method provides significance in guiding the market-oriented operation of HSR.